Shallow-water channel sounding for high speed acoustic communication

Rudander, Jacob; Husøy, Thor; Orten, Pål; Walree, Paul van

doi:10.1109/oceanse.2017.8084613

Cited by 13 publications

(3 citation statements)

References 12 publications

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“…The transmitted waveform was binary phase-shift keying (BPSK) modulated using a bit rate of 78.125 kbps and a carrier frequency of 250 kHz. For additional details of the experiment the reader is referred to [10].…”

Section: Data Collectionmentioning

confidence: 99%

Comparing RLS and LMS Adaptive Equalizers for Large Hydrophone Arrays in Underwater Acoustic Communication Channels

Rudander¹,

Husøy²,

Orten³

et al. 2019

OCEANS 2019 - Marseille

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There is an expected growth in underwater acoustic data traffic. To meet the demand of high data throughput, a migration towards the very high frequency band (>100 kHz) will be necessary. The increment in frequency comes with two problems; high propagation losses and rapid channel fluctuations.One solution addressing both of these obstacles is the use of large hydrophone arrays in combination with multi-channel equalizers. We will in this paper examine and compare tracking properties and convergence rate of the RLS and LMS adaptive algorithm for use in large multichannel equalizers.Using data from a very high frequency (250 kHz) channel we will show that in our channel, for large hydrophone arrays, RLS does not offers a significant advantage over LMS when it comes to tracking channel variations nor convergence rate.

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Section: Data Collectionmentioning

confidence: 99%

Comparing RLS and LMS Adaptive Equalizers for Large Hydrophone Arrays in Underwater Acoustic Communication Channels

Rudander¹,

Husøy²,

Orten³

et al. 2019

OCEANS 2019 - Marseille

Self Cite

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“…Due to the complex propagation environments, UWA channels show several unique characteristics. UWA channels are affected by numerous motion factors [4], [5], which can be divided into: 1) intentional platform motion, e.g., autonomous underwater vehicle's (AUV's) vehicular motion; 2) unintentional drifting platform motion caused by the movement of water; 3) surface motion, which may fluctuate with waves and show cyclic patterns [6]. Because of the low speed of sound in the water (usually about 1500 m/s), the changes of transmission delays caused by motion effects cannot be neglected [7], [8].…”

Section: Introductionmentioning

confidence: 99%

A 2D Non-Stationary Channel Model for Underwater Acoustic Communication Systems

Zhu¹,

Wang²,

Ma³

2021

Preprint

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Underwater acoustic (UWA) communication plays a key role in the process of exploring and studying the ocean. In this paper, a modified non-stationary wideband channel model for UWA communication in shallow water scenarios is proposed. In this geometry-based stochastic model (GBSM), multiple motion effects, time-varying angles, distances, clusters' locations with the channel geometry, and the ultra-wideband property are considered, which makes the proposed model more realistic and capable of supporting long time/distance simulations. Some key statistical properties are investigated, including temporal autocorrelation function (ACF), power delay profile (PDP), average delay, and root mean square (RMS) delay spread. The impacts of multiple motion factors on temporal ACFs are analyzed. Simulation results show that the proposed model can mimic the non-stationarity of UWA channels. Finally, the proposed model is validated with measurement data.

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“…Channel sounding is a technique used to ascertain the channel impulse response h(t, τ) as a function of time t and time delay τ [113,114]. This may be done by transmitting dedicated probing signals through the UWA channel.…”

Section: Channel Coherencymentioning

confidence: 99%

Code Optimisation Framework for Multicode Sonar Systems

Rashed¹

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<p>The ocean is a temporally and spatially varying environment, the characteristics of which pose significant challenges to the development of effective underwater wireless communications and sensing systems. An underwater sensing system such as a sonar detects the presence of a known signal through correlation. It is advantageous to use multiple transducers to increase surveying area with reduced surveying costs and time. Each transducers is assigned a dedicated code. When using multiple codes, the sidelobes of auto- and crosscorrelations are restricted to theoretical limits known as bounds. Sets of codes must be optimised in order to achieve optimal correlation properties, and, achieve Sidelobe Level (SLL)s as low as possible. In this thesis, we present a novel code-optimisation method to optimise code-sets with any number of codes and up to any length of each code. We optimise code-sets for a matched filter for application in a multi-code sonar system. We first present our gradient-descent based algorithm to optimise sets of codes for flat and low crosscorrelations and autocorrelation sidelobes, including conformance of the magnitude of the samples of the codes to a target power profile. We incorporate the transducer frequency response and the channel effects into the optimisation algorithm. We compare the correlations of our optimised codes with the well-known Welch bound. We then present a method to widen the autocorrelation mainlobe and impose monotonicity. In many cases, we are able to achieve SLLs beyond the Welch bound. We study the Signal to Noise Ratio (SNR) improvement of the optimised codes for an Underwater Acoustic (UWA) channel. During its propagation, the acoustic wave suffers non-constant transmission loss which is compensated by the application of an appropriate Time Variable Gain (TVG). The effect of the TVG modifies the noise received with the signal. We show that in most cases, the matched filter is still the optimum filter. We also show that the accuracy in timing is very important in the application of the TVG to the received signal. We then incorporate Doppler tolerance into the existing optimisation algorithm. Our proposed method is able to optimise sets of codes for multiple Doppler scaling factors and non-integer delays in the arrival of the reflection, while still conforming to other constraints. We suggest designing mismatched filters to further reduce the SLLs, firstly using an existing Quadratically Constrained Qaudratic Program (QCQP) formulation and secondly, as a local optimisation problem, modifying our basic optimisation algorithm.</p>

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Shallow-water channel sounding for high speed acoustic communication

Cited by 13 publications

References 12 publications

Comparing RLS and LMS Adaptive Equalizers for Large Hydrophone Arrays in Underwater Acoustic Communication Channels

Comparing RLS and LMS Adaptive Equalizers for Large Hydrophone Arrays in Underwater Acoustic Communication Channels

A 2D Non-Stationary Channel Model for Underwater Acoustic Communication Systems

Code Optimisation Framework for Multicode Sonar Systems

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